Hybrid KD-NFT: A multi-layered NFT assisted robust Knowledge Distillation framework for Internet of Things

Article


Wang, Nai, Chen, Junjun, Wu, Di, Yang, Wencheng, Xiang, Yong and Sajjanhar, Atul. 2023. "Hybrid KD-NFT: A multi-layered NFT assisted robust Knowledge Distillation framework for Internet of Things." Journal of Information Security and Applications. 75. https://doi.org/10.1016/j.jisa.2023.103483
Article Title

Hybrid KD-NFT: A multi-layered NFT assisted robust Knowledge Distillation framework for Internet of Things

Article CategoryArticle
AuthorsWang, Nai, Chen, Junjun, Wu, Di, Yang, Wencheng, Xiang, Yong and Sajjanhar, Atul
Journal TitleJournal of Information Security and Applications
Journal Citation75
Article Number103483
Number of Pages10
Year2023
Place of PublicationUnited Kingdom
Digital Object Identifier (DOI)https://doi.org/10.1016/j.jisa.2023.103483
Web Address (URL)https://www.sciencedirect.com/science/article/pii/S2214212623000674
Abstract

The Internet of Things (IoT) concept has increasingly gained popularity among different industrial and scientific fields by leveraging the development of modern electronic chip manufacturing and networking hardware and techniques. As the combination of end devices and networking techniques, it becomes more and more possible that people can organize an IoT system to serve more extensive industrial and scientific needs by running a higher level of machine learning models, such as Federated Learning (FL) and Knowledge Distillation (KD) architectures. However, security over network communications is vital when the whole system spreads to massive scales in networking, including data integrity and robustness over external malicious attacks, which would significantly affect the system's overall modal training effectiveness. In this paper, we propose an ungraded version of the Non-Fungible Token (NFT) assisted Knowledge Distillation framework, aiming at leveraging the blockchain features on data security to solve the intrinsic robustness defects in a naive KD architecture and reducing overall processing time by adding a local blockchain layer. Our major contributions can be concluded as the following (1) a revised version Hybrid KD-NFT framework from our previously proposed State-of-the-art (SOTA) framework, which improves the overall effectiveness and reduces the overall latency when compared to its original version; (2) the proposal and implementation of a hybrid (combination of private and public chain) multi-layer blockchain architecture; and (3) conducting more sets of experiments and performing more comprehensive comparisons over existing other KD frameworks in more metrics to prove our proposed Hybrid KD-NFT framework is a valid work.

KeywordsBlockchain; NFT; Knowledge Distillation; Internet of Things
ANZSRC Field of Research 2020460299. Artificial intelligence not elsewhere classified
Public Notes

Files associated with this item cannot be displayed due to copyright restrictions.

Byline AffiliationsDeakin University
Peking University, China
School of Mathematics, Physics and Computing
Permalink -

https://research.usq.edu.au/item/z2714/hybrid-kd-nft-a-multi-layered-nft-assisted-robust-knowledge-distillation-framework-for-internet-of-things

  • 10
    total views
  • 0
    total downloads
  • 3
    views this month
  • 0
    downloads this month

Export as

Related outputs

Feature extraction and learning approaches for cancellable biometrics: A survey
Yang, Wencheng, Wang, Song, Hu, Jiankun, Tao, Xiaohui and Li, Yan. 2024. "Feature extraction and learning approaches for cancellable biometrics: A survey." CAAI Transactions on Intelligence Technology. https://doi.org/10.1049/cit2.12283
VPFL: A verifiable privacy-preserving federated learning scheme for edge computing systems
Zhang, Jiale, Liu, Yue, Wu, Di, Lou, Shuai, Chen, Bing and Yu, Shui. 2023. "VPFL: A verifiable privacy-preserving federated learning scheme for edge computing systems." Digital Communications and Networks. 9 (4), pp. 981-989. https://doi.org/10.1016/j.dcan.2022.05.010
Short-term wave power forecasting with hybrid multivariate variational mode decomposition model integrated with cascaded feedforward neural networks
Ali, Mumtaz, Prasad, Ramendra, Jamei, Mehdi, Malik, Anurag, Xiang, Yong, Abdulla, Shahab, Deo, Ravinesh C., Farooque, Aitazaz A. and Labban, Abdulhaleem H.. 2023. "Short-term wave power forecasting with hybrid multivariate variational mode decomposition model integrated with cascaded feedforward neural networks." Renewable Energy. 221. https://doi.org/https://doi.org/10.1016/j.renene.2023.119773
An Adaptive Feature Fusion Network for Alzheimer’s Disease Prediction
Wei, Shicheng, Li, Yan and Yang, Wencheng. 2023. "An Adaptive Feature Fusion Network for Alzheimer’s Disease Prediction." 12th International Conference on Health Information Science (HIS 2023). Melbourne, Australia 23 - 24 Oct 2023 Germany. https://doi.org/10.1007/978-981-99-7108-4
Adaptive Regularization and Resilient Estimation in Federated Learning
Uddin, Md Palash, Xiang, Yong, Zhao, Yao, Ali, Mumtaz, Zhang, Yushu and Gao, Longxiang. 2023. "Adaptive Regularization and Resilient Estimation in Federated Learning." IEEE Transactions on Services Computing. https://doi.org/10.1109/TSC.2023.3332703
A Review of Homomorphic Encryption for Privacy-Preserving Biometrics
Yang, Wencheng, Wang, Song, Cui, Hui, Tang, Zhaohui and Li, Yan. 2023. "A Review of Homomorphic Encryption for Privacy-Preserving Biometrics." Sensors. 23 (7). https://doi.org/10.3390/s23073566
A review of multi-factor authentication in the Internet of Healthcare Things
Suleski, Tance, Ahmed, Mohiuddin, Yang, Wencheng and Wang, Eugene. 2023. "A review of multi-factor authentication in the Internet of Healthcare Things." Digital Health. 9, pp. 1-20. https://doi.org/10.1177/20552076231177144
Token-Based Biometric Enhanced Key Derivation for Authentication Over Wireless Networks
Cui, Hui, Yang, Xuechao, Yang, Wencheng, Qin, Baodong and Yi, Xun. 2023. "Token-Based Biometric Enhanced Key Derivation for Authentication Over Wireless Networks." IEEE Transactions on Network Science and Engineering. 10 (4), pp. 2347-2357. https://doi.org/10.1109/TNSE.2023.3246439
New achievements on daily reference evapotranspiration forecasting: Potential assessment of multivariate signal decomposition schemes
Ali, Mumtaz, Jamei, Mehdi, Prasad, Ramendra, Karbasi, Masoud, Xiang, Yong, Cai, Borui, Abdulla, Shahab, Farooque, Aitazaz Ahsan and Labban, Abdulhaleem H.. 2023. "New achievements on daily reference evapotranspiration forecasting: Potential assessment of multivariate signal decomposition schemes." Ecological Indicators. 155. https://doi.org/10.1016/j.ecolind.2023.111030
Multivariate data decomposition based deep learning approach to forecast one-day ahead significant wave height for ocean energy generation
Zheng, Zihao, Ali, Mumtaz, Jamei, Mehdi, Xiang, Yong, Abdulla, Shahab, Yaseen, Zaher Mundher and Farooque, Aitazaz A.. 2023. "Multivariate data decomposition based deep learning approach to forecast one-day ahead significant wave height for ocean energy generation." Renewable and Sustainable Energy Reviews. 185. https://doi.org/https://doi.org/10.1016/j.rser.2023.113645
Design data decomposition-based reference evapotranspiration forecasting model: A soft feature filter based deep learning driven approach
Zheng, Zihao, Ali, Mumtaz, Jamei, Mehdi, Xiang, Yong, Karbasi, Masoud, Yaseen, Zaher Mundher and Farooque, Aitazaz Ahsan. 2023. "Design data decomposition-based reference evapotranspiration forecasting model: A soft feature filter based deep learning driven approach." Engineering Applications of Artificial Intelligence. 121. https://doi.org/10.1016/j.engappai.2023.105984
Ensemble robust local mean decomposition integrated with random forest for short-term significant wave height forecasting
Ali, Mumtaz, Prasad, Ramendra, Xiang, Yong, Jamei, Mehdi and Yaseen, Zaher Mundher. 2023. "Ensemble robust local mean decomposition integrated with random forest for short-term significant wave height forecasting." Renewable Energy. 205, pp. 731-746. https://doi.org/https://doi.org/10.1016/j.renene.2023.01.108
Designing a Multi-Stage Expert System for daily ocean wave energy forecasting: A multivariate data decomposition-based approach
Jamei, Mehdi, Ali, Mumtaz, Karbasi, Masoud, Xiang, Yong, Ahmadianfar, Iman and Yaseen, Zaher Mundher. 2022. "Designing a Multi-Stage Expert System for daily ocean wave energy forecasting: A multivariate data decomposition-based approach ." Applied Energy. 326, pp. 1-24. https://doi.org/10.1016/j.apenergy.2022.119925
A Secure Online Fingerprint Authentication System for Industrial IoT Devices over 5G Networks
Bedari, Aseel, Wang, Song and Yang, Wencheng. 2022. "A Secure Online Fingerprint Authentication System for Industrial IoT Devices over 5G Networks." Sensors. 22 (19), pp. 1-16. https://doi.org/10.3390/s22197609
Coupled online sequential extreme learning machine model with ant colony optimization algorithm for wheat yield prediction
Ali, Mumtaz, Deo, Ravinesh C., Xiang, Yong, Prasad, Ramendra, Li, Jianxin, Farooque, Aitazaz and Yaseen, Zaher Mundher. 2022. "Coupled online sequential extreme learning machine model with ant colony optimization algorithm for wheat yield prediction." Scientific Reports. 12 (1), pp. 1-23. https://doi.org/10.1038/s41598-022-09482-5
Data Caching Optimization With Fairness in Mobile Edge Computing
Zhou, Jingwen, Chen, Feifei, He, Qiang, Xia, Xiaoyu, Wang, Rui and Xiang, Yong. 2023. "Data Caching Optimization With Fairness in Mobile Edge Computing." IEEE Transactions on Services Computing. 16 (3), pp. 1750 - 1762. https://doi.org/10.1109/TSC.2022.3197881
Multimedia security and privacy protection in the internet of things: research developments and challenges
Yang, Wencheng, Wang, Song, Hu, Jiankun and Karie, Nickson M.. 2022. "Multimedia security and privacy protection in the internet of things: research developments and challenges." International Journal of Multimedia Intelligence and Security. 4 (1), pp. 20-46. https://doi.org/10.1504/ijmis.2022.121282
A linear convolution-based cancelable fingerprint biometric authentication system
Yang, Wencheng, Wang, Song, Kang, James Jin, Johnstone, Michael N. and Bedari, Aseel. 2022. "A linear convolution-based cancelable fingerprint biometric authentication system." Computers and Security. 114, pp. 1-14. https://doi.org/10.1016/j.cose.2021.102583
A Review on Security Issues and Solutions of the Internet of Drones
Yang, Wencheng, Wang, Song, Yin, Xuefei, Wang, Xu and Hu, Jiankun. 2022. "A Review on Security Issues and Solutions of the Internet of Drones." IEEE Open Journal of the Computer Society. 3, pp. 96-110. https://doi.org/10.1109/OJCS.2022.3183003
Network Forensics in the Era of Artificial Intelligence
Yang, Wencheng, Johnstone, Michael N., Wang, Song, Karie, Nickson M., Bin Sahri, Nor Masri and Kang, James Jin. 2022. "Network Forensics in the Era of Artificial Intelligence." Ahmed, Mohiuddin, Islam, Sheikh Rabiul, Anwar, Adnan, Moustafa, Nour and Pathan, Al-Sakib Khan (ed.) Explainable Artificial Intelligence for Cyber Security: Next Generation Artificial Intelligence. Cham, Switzerland. Springer. pp. 171-190
Leveraging Artificial Intelligence Capabilities for Real-Time Monitoring of Cybersecurity Threats
Karie, Nickson M., Bin Sahri, Nor Masri Bin, Yang, Wencheng and Johnstone, Michael N.. 2022. "Leveraging Artificial Intelligence Capabilities for Real-Time Monitoring of Cybersecurity Threats." Ahmed, Mohiuddin, Islam, Sheikh Rabiul, Anwar, Adnan, Moustafa, Nour and Pathan, Al-Sakib Khan (ed.) Explainable Artificial Intelligence for Cyber Security: Next Generation Artificial Intelligence. Cham, Switzerland. Springer. pp. 141-169
Variational mode decomposition based random forest model for solar radiation forecasting: New emerging machine learning technology
Ali, Mumtaz, Prasad, Ramendra, Xiang, Yong, Khan, Mohsin, Farooque, Aitazaz Ahsan, Zong, Tianrui and Yaseen, Zaher Mundher. 2021. "Variational mode decomposition based random forest model for solar radiation forecasting: New emerging machine learning technology." Energy Reports. 7, pp. 6700-6717. https://doi.org/10.1016/j.egyr.2021.09.113
Advanced extreme learning machines vs. deep learning models for peak wave energy period forecasting: A case study in Queensland, Australia
Ali, Mumtaz, Prasad, Ramendra, Xiang, Yong, Sankaran, Adarsh, Deo, Ravinesh C., Xiao, Fuyuan and Zhu, Shuyu. 2021. "Advanced extreme learning machines vs. deep learning models for peak wave energy period forecasting: A case study in Queensland, Australia." Renewable Energy. 177, pp. 1033-1044. https://doi.org/10.1016/j.renene.2021.06.052
Self-supervised cross-iterative clustering for unlabeled plant disease images
Fang, Uno, Li, J., Lu, X., Gao, Longxiang, Ali, Mumtaz and Xiang, Yong. 2021. "Self-supervised cross-iterative clustering for unlabeled plant disease images." Neurocomputing. 456, pp. 36-48. https://doi.org/10.1016/j.neucom.2021.05.066
Forecasting long-term precipitation for water resource management: a new multi-step data-intelligent modelling approach
Ali, Mumtaz, Deo, Ravinesh C., Xiang, Yong, Li, Ya and Yaseen, Zaher Mundher. 2020. "Forecasting long-term precipitation for water resource management: a new multi-step data-intelligent modelling approach." Hydrological Sciences Journal. 65 (16), pp. 2693-2708. https://doi.org/10.1080/02626667.2020.1808219
Near real-time significant wave height forecasting with hybridized multiple linear regression algorithms
Ali, Mumtaz, Prasad, Ramendra, Xiang, Yong and Deo, Ravinesh C.. 2020. "Near real-time significant wave height forecasting with hybridized multiple linear regression algorithms." Renewable and Sustainable Energy Reviews. 132. https://doi.org/10.1016/j.rser.2020.110003
A double decomposition-based modelling approach to forecast weekly solar radiation
Prasad, Ramendra, Ali, Mumtaz, Xiang, Yong and Khan, Huma. 2020. "A double decomposition-based modelling approach to forecast weekly solar radiation." Renewable Energy. 152, pp. 9-22. https://doi.org/10.1016/j.renene.2020.01.005
Complete ensemble empirical mode decomposition hybridized with random forest and kernel ridge regression model for monthly rainfall forecasts
Ali, Mumtaz, Prasad, Ramendra, Xiang, Yong and Yaseen, Z.. 2020. "Complete ensemble empirical mode decomposition hybridized with random forest and kernel ridge regression model for monthly rainfall forecasts." Journal of Hydrology. 584, pp. 1-15. https://doi.org/10.1016/j.jhydrol.2020.124647
On addressing the imbalance problem: a correlated KNN approach for network traffic classification
Wu, Di, Chen, Xiao, Chen, Chao, Zhang, Jun, Xiang, Yang and Zhou, Wanlei. 2015. "On addressing the imbalance problem: a correlated KNN approach for network traffic classification." NSS 2014: 8th International Conference on Network and System Security. Xi'an, China 15 - 17 Oct 2014 Switzerland . Springer. https://doi.org/10.1007/978-3-319-11698-3_11
Detecting stepping stones by abnormal causality probability
Wen, Sheng, Wu, Di, Li, Ping, Xiang, Yang, Zhou, Wanlei and Wei, Guiyi. 2015. "Detecting stepping stones by abnormal causality probability." Security and Communication Networks. 8 (10), pp. 1831-1844. https://doi.org/10.1002/sec.1037
A Survey on Latest Botnet Attack and Defense
Zhang, Lei, Yu, Shui, Wu, Di and Watters, Paul. 2011. "A Survey on Latest Botnet Attack and Defense ." 10th IEEE International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom 2011). Changsha, China 16 - 18 Nov 2011 China. https://doi.org/10.1109/TrustCom.2011.11